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Epilepsy is one of the most common and yet diverse set of chronic neurological disorders. This excessive or synchronous neuronal activity is termed seizure. Electroencephalogram signal processing plays a significant role in detection and…

Signal Processing · Electrical Eng. & Systems 2021-09-29 Paul Grant , Md Zahidul Islam

Seizures are one of the defining symptoms in patients with epilepsy, and due to their unannounced occurrence, they can pose a severe risk for the individual that suffers it. New research efforts are showing a promising future for the…

Machine Learning · Computer Science 2021-08-09 Carlos H. Mendoza-Cardenas , Austin J. Brockmeier

Stochastic reaction-diffusion equations are a popular modelling approach for studying interacting populations in a heterogeneous environment under the influence of environmental fluctuations. Although the theoretical basis of alternative…

Populations and Evolution · Quantitative Biology 2017-02-16 Ivo Siekmann , Michael Bengfort , Horst Malchow

The neural mechanism of memory has a very close relation with the problem of representation in artificial intelligence. In this paper a computational model was proposed to simulate the network of neurons in brain and how they process…

Neurons and Cognition · Quantitative Biology 2020-12-02 Hui Wei

Vagus Nerve Stimulation (VNS) is an established palliative treatment for drug resistant epilepsy. While effective for many patients, its mechanism of action is incompletely understood. Predicting individuals' response, or optimum…

Neurons and Cognition · Quantitative Biology 2024-06-06 John F. Ingham , Frances Hutchings , Paolo Zuliani , Yujiang Wang , Sadegh Soudjani , Peter N. Taylor

We exhibit a mathematical framework to represent the neural dynamics at cortical level. Our description of neural dynamics with columnar and functional modularity, named fibre bundle representation (FBM) method, is based both on…

Neurons and Cognition · Quantitative Biology 2007-05-23 Myoung Won Cho , Seunghwan Kim

We explore the behaviour of an ensemble of chaotic oscillators coupled only to an external chaotic system, whose intrinsic dynamics may be similar or dissimilar to the group. Counter-intuitively, we find that a dissimilar external system…

Chaotic Dynamics · Physics 2017-01-23 Sudhanshu Shekhar Chaurasia , Sudeshna Sinha

We perform an asymptotic analysis of general particle systems arising in collective behavior in the limit of large self-propulsion and friction forces. These asymptotics impose a fixed speed in the limit, and thus a reduction of the…

Analysis of PDEs · Mathematics 2012-03-01 Mihai Bostan , J. A. Carrillo

We consider a population dynamics model coupling cell growth to a diffusion in the space of metabolic phenotypes as it can be obtained from realistic constraints-based modelling. In the asymptotic regime of slow diffusion, that coincides…

Populations and Evolution · Quantitative Biology 2017-02-17 Daniele De Martino , Davide Masoero

Seizure events can manifest as transient disruptions in the control of movements which may be organized in distinct behavioral sequences, accompanied or not by other observable features such as altered facial expressions. The analysis of…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 David Ahmedt-Aristizabal , Mohammad Ali Armin , Zeeshan Hayder , Norberto Garcia-Cairasco , Lars Petersson , Clinton Fookes , Simon Denman , Aileen McGonigal

Emotional disorders and psychological flourishing are the result of complex interactions between positive and negative affects that depend on external events and the subject's internal representations. Based on psychological data, we…

Applications · Statistics 2015-05-19 Jonathan Touboul , Alberto Romagnoni , Robert Schwartz

Chaos provides many interesting properties that can be used to achieve computational tasks. Such properties are sensitivity to initial conditions, space filling, control and synchronization. Chaotic neural models have been devised to…

Neural and Evolutionary Computing · Computer Science 2015-01-12 M. Alhawarat , T. Olde Scheper , N. T. Crook

We find that sensory noise delivered together with a weak periodic signal not only enhances nonlinear response of neuronal networks, but also improves the synchronization of the response to the signal. We reveal this phenomenon in neuronal…

Neurons and Cognition · Quantitative Biology 2015-08-25 M. A. Lopes , K. -E. Lee , A. V. Goltsev , J. F. F. Mendes

Much progress has been made in uncovering the computational capabilities of spiking neural networks. However, spiking neurons will always be more expensive to simulate compared to rate neurons because of the inherent disparity in time…

Neurons and Cognition · Quantitative Biology 2013-10-31 Michael A. Buice , Carson C. Chow

We investigated how the stability of macroscopic states in the associative memory model is affected by synaptic depression. To this model, we applied the dynamical mean-field theory, which has recently been developed in stochastic neural…

Disordered Systems and Neural Networks · Physics 2010-05-24 Yosuke Otsubo , Kenji Nagata , Masafumi Oizumi , Masato Okada

We carry out a comprehensive linear stability analysis of active Brownian particle systems around a constant homogeneous state. These scalar models, being important prototypes for the continuous description of active matter, are…

Analysis of PDEs · Mathematics 2025-12-22 Michele Coti Zelati , Lucas Ertzbischoff , David Gerard-Varet

We study the stabilization of coherent suppression of tunneling in a driven double-well system subject to random periodic $\delta-$function ``kicks''. We model dissipation due to this stochastic process as a phase diffusion process for an…

Quantum Physics · Physics 2009-11-06 J. Grondalski , P. M. Alsing , I. H. Deutsch

Diffusion theory establishes a fundamental connection between stochastic differential equations and partial differential equations. The solution of a partial differential equation known as the Fokker-Planck equation describes the…

Probability · Mathematics 2025-10-24 Carlos Escudero , Helder Rojas

Real time seizure detection is a fundamental problem in computational neuroscience towards diagnosis and treatment's improvement of epileptic disease. We propose a real-time computational method for tracking and detection of epileptic…

Quantitative Methods · Quantitative Biology 2024-06-17 Ximena Fernández , Diego Mateos

The computation performed by a neuron can be formulated as a combination of dimensional reduction in stimulus space and the nonlinearity inherent in a spiking output. White noise stimulus and reverse correlation (the spike-triggered average…

Biological Physics · Physics 2007-05-23 Blaise Aguera y Arcas , Adrienne Fairhall